I have asked some participants (29) to complete several tasks, and I have the results for the people that successfully completed it, and those who didn't. I have a breakdown by age (4 groups) and I am trying to prove ($H_0$) that age is independent for the successful completion of the task.

I am trying to understand whether I have to use chi square or ANOVA. I used anova and I was able to reject the $H_0$, but if I use Chi Square, I fail to reject the Nullhypothesis.

Can someone guide me on this, please?

  • $\begingroup$ Could you please clarify if your dependent variable is a count (number of completed tasks) or a binary feature (completed/not completed)? $\endgroup$ Aug 30, 2017 at 15:11
  • $\begingroup$ Hi, thanks a lot for your reply! It was a task that they had to do and they would either get a success or unsuccess. Therefore, it is a binary feature. Thanks again $\endgroup$ Aug 30, 2017 at 15:43

1 Answer 1


ANOVA is better suited for real-valued dependent variables, so in your case chi-square test is a better alternative. If you are doing this in R, you could use prop.test, it implements the same chi-squared when there are more than two groups (age groups, in your case).

  • $\begingroup$ Thanks a lot for your help, I appreciate it. I had also two other analysis, male-female success-unsuccess, and experience-not, success-unsuccess. Since those are tables 2 x 2 and with the kind of binary feature I had, I used chi square. Do you think that is OK, or you recommend something else? $\endgroup$ Aug 31, 2017 at 8:33
  • $\begingroup$ It's fine! There are other alternatives like tests for proportion, but chi-squared is perfectly valid as well. $\endgroup$ Aug 31, 2017 at 9:39
  • $\begingroup$ Thanks a lot for your help! Last question if I may ask. Thanks again! I am trying now to compare the results I got as metrics. The 29 participants would do specific tasks on 3 different websites. I have the average time that it took to complete each task on each website and the target. Can I do ANOVA to check if there is a significant difference between target vs website 1, 2, and 3? Or there is a better tool to compare the TARGET vs the real time it took? Thanks again $\endgroup$ Aug 31, 2017 at 10:05
  • $\begingroup$ Most likely ANOVA would do, but you have to be careful choosing between-subjects or within-subjects ANOVA. Do you have the same 29 participants doing the task on each of the 3 websites, or are they distributed between different websites? In the first case it is within-subjects ANOVA (or, as a nonparametric alternative, Friedman rank sum test); in the second ANOVA should be between-subjects (or you could use Kruskal-Wallis test). $\endgroup$ Aug 31, 2017 at 15:06
  • $\begingroup$ Thanks so much! I thought it would be ANOVA and now that I have your confirmation I will get to it. It is indeed 29 people doing all the 6 tasks; i didn't divide them. So I will use the within subject ANOVA. In one column I will put the target time and on the other one all the actual times. Does it sound right? Thank you!!!!! $\endgroup$ Aug 31, 2017 at 16:09

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